Teams Engineer

Role: Platform Engineer Duration: 1 month Location: St. Louis, MO

Role Overview Highly skilled AI Infrastructure Engineer to design, build, and operate scalable GPU-enabled Kubernetes platforms for AI/ML workloads.

Kubernetes, Linux, Terraform, GPUs and NVIDIA stack

3 8+ years' experience Strong Kubernetes knowledge Experience with GPUs and NVIDIA stack Linux (Ubuntu) expertise Experience with Terraform

Longhorn or Ceph experience Canonical ecosystem (MAAS, Juju) AI/ML tools like Kubeflow Certifications (CKA, NVIDIA)

Strong problem-solving and troubleshooting mindset Ability to collaborate with cross-functional teams (ML engineers, data scientists) Clear communication and documentation skills Passion for automation and platform scalability

• Design and manage Kubernetes clusters
• Build GPU-enabled infrastructure
• Deploy Longhorn storage
• Automate infrastructure using Terraform
• Monitor systems using Prometheus and Grafana

Knowledge Transfer & Client Enablement Provide structured knowledge transfer (KT) sessions to client teams on all core platform components, including: Kubernetes architecture, operations, and troubleshooting GPU infrastructure (NVIDIA stack, scheduling, resource optimization) Longhorn storage management and performance tuning Canonical ecosystem tools (MAAS, Juju, Charmed Kubernetes) Develop and deliver technical documentation, runbooks, and training materials to support ongoing operations Conduct hands-on workshops and guided sessions to enable client teams to independently manage and scale the platform Act as a technical advisor, helping client stakeholders understand best practices in: Cloud-native infrastructure o AI/ML platform operations o Reliability, performance, and cost optimization Ensure smooth handoff of production systems with full operational readiness and support knowledge

For applications and inquiries,